This invention relates to a speech coding system and, in particular, relates to a speech coding system which is suitable for use in communication systems on which a severe limitation is imposed on the frequency band and the transmitting power.
In communication systems on which these limitations are imposed, such as digital maritime satellite communication systems or SCPC, a speech coding system is required such that the coded speech signal of high performance and low bit rate can be obtained. Speech quality of the reproduced speech is high in spite of the presence of transmission code errors.
In view of this technical background, 16 kb/s adaptive predictive coding (APC) of speech signal has been proposed.
FIG. 1 shows one example of the prior APC systems, referred to as pre-emphasis/de-emphasis method. This system is so designed that the power of the quantization noise is kept low in a relatively high frequency voiceband, when compared with the power of the speech signal. Thus, the hiss noise is reduced and the speech quality in the reproduced speech is improved.
In FIG. 1, a digital voiceband signal, or successive speech samples are provided to a coder input terminal 1 through an analog bandpass filter and an analog-digital converter (both of them not shown). A pre-emphasis circuit 2 emphasizes the power of the signal components with relatively high frequency. A spectrum analyzer 3 analyzes the spectrum of the signal from the pre-emphasis circuit 2 at every frame whose duration is equal to 20 ms for example, and then calculates predictor coefficients for a short-term spectrum predictor 4 denoted by P(z). The short-term predictor 4, with the predictor coefficients, calculates a prediction value for the current sample of the speech signal. A subtractor 5 provides a residual error signal by calculating the difference between the prediction value and the current sample. Then, an adaptive quantizer 6 quantizes the residual signal. An adaptive inverse quantizer 7 inversely quantizes the quantized residual signal. An adder 8 adds the reconstructed residual signal provided by the inverse quantizer 7 to the prediction value. The output of the adder 8 is provided to the short-term predictor 4, which calculates the next prediction value. The quantized residual signal from the quantizer 6 and the predictor coefficients from the spectrum analyzer 3 are coded and then multiplexed by a multiplexer 9. The multiplexed signal is transmitted to a decoder through a coder output terminal 10.
The transmitted signal is input at input terminal 11 and demultiplexed by demultiplexer into the quantized residual signal and the predictor coefficients. The quantized residual signal is inversely quantized by an adaptive inverse quantizer 13, which provides the reconstructed residual signal to one of the inputs of an adder 15. On the other hand the, predictor coefficients are provided to a short-term spectrum predictor 14 denoted by P(z). It calculates a prediction value for the present sample based on the past reconstructed samples. The adder 15 adds the prediction value to the current sample. The output of the adder 15 is provided to the input of the predictor 14 to calculate the prediction value for the next sample. The output of the adder 15 is also provided to a de-emphasis circuit 16, which provides a decoded speech signal to a decoder output terminal 18. This speech signal is then reproduced through a digital-analog converter and an analog bandpass filter (both of them not shown). As shown in FIG. 1, the pre-emphasis circuit 2 consists of a digital filter 2' denoted by G(z) and a subtractor 2". The de-emphasis circuit 16 consists of a digital filter 16' denoted by G(z) and an adder 16".
In this prior coding system, the use of the pre-emphasis circuit 2 and the de-emphasis circuit 16 makes it possible to improve speech quality in the reproduced speech. In other words, the quantization noise component in relatively high frequency band is kept low, and thus the hiss noise in such a frequency band is reduced.
However, this prior system has the disadvantage that the characteristics of the pre-emphasis and the de-emphasis circuits 2 and 16 are not always adaptive to the properties of the speech signal because the digital filters 2' and 16' use the fixed predictor coefficients.
FIG. 2 shows an another prior speech coding system. The feature of this prior system is the use of a noise shaping filter 22 which is so designed that the spectrum of the quantization noise which is approximately white is adaptively shaped so as to correspond to the spectrum of the input speech signal.
In this figure, at the output of the subtractor 5, there is provided the residual signal. A subtractor 23 provides a final residual signal by calculating the difference between the residual signal and the output of the noise shaping filter 22 denoted by P(z). The final residual signal is quantized by the adaptive quantizer 6. The quantized final residual signal is inversely quantized by the adaptive inverse quantizer 7, which provides a reconstructed final residual signal. Then, a quantization noise is provided by calculating the difference between the constructed final residual signal and the final residual signal from the subtractor 23. The quantization noise is then provided to the noise shaping filter 22.
The noise shaping filter 22 consists of digital filters and its transfer function can be expressed in the Z-transform notation as ##EQU1## where F(z) is the frequency response of the noise shaping filter, N is the tap number of the filter 22, a.sub.i is a predictor coefficient of i-th tap and r is a constant in the region of 0 to 1. The value r is selected so that speech quality in the reproduced speech is improved.
However, the prior speech coding system of FIG. 2 has the following disadvantages.
(1) The prepared quantization characteristics of the adaptive quantizer 6 is not perfectly suitable for the properties of the final residual signal such as the amplitude distribution and/or the power, because the output of the noise shaping filter 22 is returned to the input of the adaptive quantizer 6. In other words, it is impossible to prepare the quantization characteristics suitable for the properties of the final residual signal. Thus, the quantization noise increases.
(2) The combination of the adder 15 and the short-term predictor 14 forms a recursive digital filter. It should be noted that the output of the adder 15 is returned to the input of the predictor 14. On the other hand, the predictor coefficients to be set in the predictor 14 are the optimum coefficients to predict the present value of the residual signal from the inverse quantizer 13. Thus, when the transmitted signal has the transmission code error due to, for example, fading, the recursive filter is apt to oscillate, or sometimes oscillates. Therefore, speech quality in the reproduced speech deteriorates considerably.